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aws-microservices icon aws-microservices

AWS Serverless Event-driven Microservices with using AWS Lambda, AWS DynamoDB, AWS API Gateway, AWS EventBridge, AWS SQS, AWS CDK stands for Cloud Development Kit for IaC — Infrastructure as Code tool and AWS CloudWatch for monitoring.

azure-zero-to-hero icon azure-zero-to-hero

Repository to learn Azure from Zero. This repository covers the complete Azure fundamentals required for a DevOps Engineer.

eda-hotel-booking-analysis icon eda-hotel-booking-analysis

Conducted exploratory data analysis on the provided dataset and derived valuable conclusions about broad hotel booking trends and how various factors interact to affect hotel bookings. Created dashboard using Tableau.

eda_hotel_booking_analysis icon eda_hotel_booking_analysis

Exploratory Data Analysis of Hotel Booking A hotel booking is a process that enables guests to schedule dates & length of stay, room selection, extras and payment all in one place. Hotel bookings can be done through several ways like Direct, Online/Offline TA/TO etc. We were provided with Hotel Bookings data set to analyze & gain Insights from it

gke-private-cluster-demo icon gke-private-cluster-demo

This guide demonstrates creating a Kubernetes private cluster in Google Kubernetes Engine (GKE) running a sample Kubernetes workload that connects to a Cloud SQL instance using the cloud-sql-proxy "sidecar" authenticated using Workload Identity (Beta).

global-terrorism-analysis icon global-terrorism-analysis

The project analyses and visualises global terrorist attacks over the time frame of 1970 to 2019. Points out and analyses trends of over 2,00,000 terror attacks, their attackers and studies various other features

grafana icon grafana

Grafana using Kube-Prometheus-Stack

netflix-movies-and-tv-shows-clustering-ml-unsupervised icon netflix-movies-and-tv-shows-clustering-ml-unsupervised

The Netflix Movies and TV Shows Clustering Project aims to cluster similar movies and TV shows available on Netflix into different clusters based on their content. The project uses Natural Language Processing (NLP) and unsupervised machine learning techniques to analyze the dataset, including K-Means, Hierarchical clustering, and DBSCAN algorithms.

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